Aureonics: Constitutional Triadic Framework for Stable Adaptive Intelligence
Emmanuel King · Independent Research · 2025
We present Aureonics, a constitutional triadic framework for stable adaptive intelligence. The framework models AI system health as a probability simplex over three irreducible invariants: Continuity (C), Reciprocity (R), and Sovereignty (S), constrained such that C+R+S=1. The stability margin M=min(C,R,S) provides a scalar measure of constitutional health. We introduce the Dynamic CRS Governor — a Control Barrier Function-based control system that detects constitutional drift before failure and applies mass-conserving corrections to restore stability. The framework is operationalized into a five-agent PRAXIS pipeline with cryptographic audit receipts, Lyapunov stability certificates, and real-time constitutional monitoring. We demonstrate that the system is mathematically bounded, falsifiable, and deployable as a governance layer for production language models.
C + R + S = 1Constitutional simplex constraint — state always normalized on probability simplex
M = min(C, R, S)Stability margin — system is only as stable as its weakest invariant
M < τ = 0.08Hard collapse threshold — CBF governor fires and applies correction
ḣ(x) + α·h(x) ≥ 0Control Barrier Function constraint — always enforced during projection
‖dx/dt‖ > δVelocity trigger — detects rapid constitutional drift before collapse
V(x) = ‖x - x*‖²Lyapunov candidate — stability certificate, δV < 0 guarantees convergence
@article{king2025aureonics,
title = {Aureonics: Constitutional Triadic Framework
for Stable Adaptive Intelligence},
author = {King, Emmanuel},
year = {2025},
doi = {10.5281/zenodo.18944243},
url = {https://doi.org/10.5281/zenodo.18944243},
note = {Independent Research, Lagos, Nigeria}
}